package intensivecomp.examples;

import java.io.IOException;
import java.util.StringTokenizer;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

public class WordCount {
    //继承mapper接口，设置map的输入类型为<Object,Text>
    //输出类型为<Text,IntWritable>
    public static class Map extends Mapper<Object,Text,Text,IntWritable>{
        //one表示单词出现一次
        private static IntWritable one = new IntWritable(1);
        //word存储切下的单词
        private Text word = new Text();
        public void map(Object key,Text value,Context context) throws IOException,InterruptedException{
            //对输入的行切词
            StringTokenizer st = new StringTokenizer(value.toString());
            while(st.hasMoreTokens()){
                word.set(st.nextToken());//切下的单词存入word
                context.write(word, one);
            }
        }
    }
    //继承reducer接口，设置reduce的输入类型<Text,IntWritable>
    //输出类型为<Text,IntWritable>
    public static class Reduce extends Reducer<Text,IntWritable,Text,IntWritable>{
        //result记录单词的频数
        private static IntWritable result = new IntWritable();
        public void reduce(Text key,Iterable<IntWritable> values,Context context) throws IOException,InterruptedException{
            int sum = 0;
            //对获取的<key,value-list>计算value的和
            for(IntWritable val:values){
                sum += val.get();
            }
            //将频数设置到result
            result.set(sum);
            //收集结果
            context.write(key, result);
        }
    }
    /**
     * @param args
     */
    public static void main(String[] args) throws Exception{
        Configuration conf = new Configuration();
        conf.set("mapred.remote.os","Linux");
        conf.set("yarn.resourcemanager.address","master:8032");
        conf.set("mapreduce.framework.name","yarn");
        conf.set("mapreduce.job.jar","D:\\workspace\\Hadoop\\hadoop\\out\\artifacts\\hadoop_jar\\hadoop.jar");
        conf.set("mapreduce.app-submission.cross-platform","true");
        conf.set("fs.defaultFS", "hdfs://master:9000");
        Job job = Job.getInstance(conf);
        job.setJobName("word count");
        //配置作业各个类
        job.setJarByClass(WordCount.class);
        job.setMapperClass(Map.class);
        job.setCombinerClass(Reduce.class);
        job.setReducerClass(Reduce.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);
        FileInputFormat.addInputPath(job, new Path("hdfs://master:9000/tmp/test.txt"));
        FileOutputFormat.setOutputPath(job, new Path("hdfs://master:9000/tmp/out"));
        System.exit(job.waitForCompletion(true) ? 0 : 1);
    }

}